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 },
 "nbformat": 3,
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "id": "49EF10225D5446198FA3ED76843A1EE6",
     "metadata": {},
     "source": [
      "\u6211\u4eec\u4ee5\u7b80\u5355\u7684\u53cc\u5747\u7ebf\u7a81\u7834\u7b56\u7565\u4e3a\u4f8b\uff0c\u6765\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u4f18\u77ff\u4e13\u4e1a\u7248\u7684\u7ec4\u5408\u5206\u6790\u5de5\u5177\u8fdb\u884c\u7b56\u7565\u5206\u6790"
     ]
    },
    {
     "cell_type": "strategy",
     "collapsed": false,
     "has_detail": true,
     "id": "1DF70B054C4F4CA5A03902E4F5784DB2",
     "input": "import talib\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n### \u53c2\u6570\u521d\u59cb\u5316\nuniverse = ['RB1610']               # \u7b56\u7565\u8bc1\u5238\u6c60\nstart = pd.datetime(2016, 6, 1)   # \u56de\u6d4b\u5f00\u59cb\u65f6\u95f4\nend   = pd.datetime(2016, 9, 1)   # \u56de\u6d4b\u7ed3\u675f\u65f6\u95f4\ncapital_base = 1e4                  # \u521d\u8bd5\u53ef\u7528\u8d44\u91d1\nrefresh_rate = 1                  # \u8c03\u4ed3\u5468\u671f\nfreq = 'd'                          # \u8c03\u4ed3\u9891\u7387\uff1as -> \u79d2\uff1bm-> \u5206\u949f\uff1bd-> \u65e5\uff1b\n\n## \u81ea\u52a8\u751f\u6210\u4fdd\u8bc1\u91d1\u6bd4\u4f8b\uff1a margin_rate\nmargin_ratio = DataAPI.FutuGet(ticker = universe, field = ['ticker','tradeMarginRatio'], pandas = '1')\nmargin_rate = dict(zip(margin_ratio.ticker.tolist(), [0.01*index for index in margin_ratio.tradeMarginRatio.tolist()]))\naccounts = {\n    'futures_account': AccountConfig(account_type='futures', capital_base=capital_base, margin_rate=margin_rate)\n}\n\n### \u7b56\u7565\u521d\u59cb\u5316\u51fd\u6570\uff0c\u4e00\u822c\u7528\u4e8e\u8bbe\u7f6e\u8ba1\u6570\u5668\uff0c\u56de\u6d4b\u8f85\u52a9\u53d8\u91cf\u7b49\u3002\ndef initialize(context):\n    pass\n\n### \u56de\u6d4b\u8c03\u4ed3\u903b\u8f91\uff0c\u6bcf\u4e2a\u8c03\u4ed3\u5468\u671f\u8fd0\u884c\u4e00\u6b21\uff0c\u53ef\u5728\u6b64\u51fd\u6570\u5185\u5b9e\u73b0\u4fe1\u53f7\u751f\u4ea7\uff0c\u751f\u6210\u8c03\u4ed3\u6307\u4ee4\u3002\ndef handle_data(context):\n    futures_account = context.get_account('futures_account')\n    symbol, amount = universe[0], 1\n    history_data = context.history(symbol = symbol, time_range = 20)[symbol]\n    MA_S = talib.MA(history_data['closePrice'].apply(float).values, timeperiod = 5)\n    MA_L = talib.MA(history_data['closePrice'].apply(float).values, timeperiod = 10)\n\n    current_long = futures_account.get_positions().get(symbol, dict()).get('long_amount', 0)\n    current_short = futures_account.get_positions().get(symbol, dict()).get('short_amount', 0)    \n    if MA_S[-1] > MA_L[-1] and MA_S[-2] < MA_L[-2]:\n        if current_short > 0:\n            # print futures_account.current_date, futures_account.current_time, '\u4e70\u5165\u5e73\u4ed3'\n            futures_account.order(symbol, current_short, 'close')\n        if current_long < amount:\n            # print futures_account.current_date, futures_account.current_time, '\u4e70\u5165\u5f00\u4ed3'\n            futures_account.order(symbol, amount, 'open')\n            \n    if MA_S[-1] < MA_L[-1] and MA_S[-2] > MA_L[-2]:\n        if current_long > 0:\n            # print futures_account.current_date, futures_account.current_time,'\u5356\u51fa\u5e73\u4ed3'\n            futures_account.order(symbol, -current_long, 'close')\n        if current_short < amount:\n            # print futures_account.current_date, futures_account.current_time, '\u5356\u51fa\u5f00\u4ed3'\n            futures_account.order(symbol, -amount, 'open')",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": "'{\"information\": 1.30424, \"benchmark_cumulative_return\": {\"1470787200000\": 0.0232779944, \"1468972800000\": 0.0214682795, \"1466035200000\": -0.0236263078, \"1464912000000\": 0.0062361968, \"1468368000000\": 0.0357488106, \"1467072000000\": -0.0104617045, \"1467590400000\": 0.0110854503, \"1471564800000\": 0.0616678656, \"1465862400000\": -0.0295236563, \"1472428800000\": 0.0436088921, \"1466467200000\": -0.0199529272, \"1469059200000\": 0.0261749265, \"1470700800000\": 0.0275814309, \"1468281600000\": 0.0326928659, \"1466121600000\": -0.0186786179, \"1466553600000\": -0.0112315274, \"1468886400000\": 0.0248217418, \"1468800000000\": 0.0291718724, \"1465171200000\": 0.0029114451, \"1467849600000\": 0.0127443557, \"1468540800000\": 0.0336696576, \"1469577600000\": 0.0153595452, \"1470096000000\": 0.006150065, \"1470960000000\": 0.0393347973, \"1472601600000\": 0.0499230177, \"1472515200000\": 0.0449358902, \"1469404800000\": 0.0193481114, \"1464825600000\": -0.000776133, \"1472688000000\": 0.0416515226, \"1466726400000\": -0.0291538889, \"1468454400000\": 0.0338229912, \"1470614400000\": 0.0203886344, \"1469664000000\": 0.0162726057, \"1465776000000\": -0.0325657189, \"1468195200000\": 0.0106544757, \"1467244800000\": -0.0049341233, \"1470009600000\": 0.0022870682, \"1471996800000\": 0.0505757897, \"1466985600000\": -0.0154646071, \"1467763200000\": 0.0149055389, \"1470268800000\": 0.0100105377, \"1471305600000\": 0.065840369, \"1469750400000\": 0.0108437764, \"1465344000000\": -0.0017586037, \"1471219200000\": 0.0706293618, \"1467158400000\": -0.0057326569, \"1467331200000\": -0.0048460985, \"1470355200000\": 0.0112160678, \"1471478400000\": 0.0614990724, \"1466640000000\": -0.0164827295, \"1471824000000\": 0.0527628441, \"1465948800000\": -0.0167821401, \"1472169600000\": 0.0433908808, \"1466380800000\": -0.0179476016, \"1472083200000\": 0.043984654, \"1471392000000\": 0.0642007092, \"1470873600000\": 0.0201289769, \"1464739200000\": -0.0028436124, \"1465257600000\": 0.002364366, \"1469145600000\": 0.017542498, \"1471910400000\": 0.0543513926, \"1467676800000\": 0.0119332021, \"1469491200000\": 0.0315589546, \"1470182400000\": 0.0075553074, \"1467936000000\": 0.0071681874}, \"benchmark_annualized_return\": 0.16994, \"turnover_rate\": 0.0, \"max_drawdown\": 0.31372, \"beta\": 0.35122, \"sharpe\": 1.92034, \"alpha\": 1.03837, \"volatility\": 0.5654, \"annualized_return\": 1.12077, \"cumulative_return\": {\"1470787200000\": 0.1011031, \"1468972800000\": 0.15353364, \"1466035200000\": 0.13391216, \"1464912000000\": 0.02791216, \"1468368000000\": 0.39753364, \"1467072000000\": 0.11253364, \"1467590400000\": 0.25953364, \"1471564800000\": 0.0711031, \"1465862400000\": 0.17291216, \"1472428800000\": 0.1328727, \"1466467200000\": 0.0687274, \"1469059200000\": 0.11232584, \"1470700800000\": 0.1061031, \"1468281600000\": 0.33853364, \"1466121600000\": 0.10191216, \"1466553600000\": 0.0387274, \"1468886400000\": 0.16253364, \"1468800000000\": 0.28653364, \"1465171200000\": 0.07891216, \"1467849600000\": 0.24853364, \"1468540800000\": 0.36053364, \"1469577600000\": 0.06032584, \"1470096000000\": 0.0151031, \"1470960000000\": 0.0891031, \"1472601600000\": 0.1738727, \"1472515200000\": 0.1428727, \"1469404800000\": 0.13432584, \"1464825600000\": 0.0, \"1472688000000\": 0.2158727, \"1466726400000\": -0.01246636, \"1468454400000\": 0.35853364, \"1470614400000\": 0.0851031, \"1469664000000\": 0.00332584, \"1465776000000\": 0.20191216, \"1468195200000\": 0.26953364, \"1467244800000\": 0.14253364, \"1470009600000\": -0.0188969, \"1471996800000\": 0.0838727, \"1466985600000\": 0.05753364, \"1467763200000\": 0.21853364, \"1470268800000\": -0.0238969, \"1471305600000\": 0.1441031, \"1469750400000\": -0.0408969, \"1465344000000\": 0.12791216, \"1471219200000\": 0.0661031, \"1467158400000\": 0.09753364, \"1467331200000\": 0.19153364, \"1470355200000\": 0.0201031, \"1471478400000\": 0.0951031, \"1466640000000\": 0.0087274, \"1471824000000\": 0.0948727, \"1465948800000\": 0.12291216, \"1472169600000\": 0.0938727, \"1466380800000\": 0.12191216, \"1472083200000\": 0.0888727, \"1471392000000\": 0.1441031, \"1470873600000\": 0.0871031, \"1464739200000\": 0.0, \"1465257600000\": 0.12191216, \"1469145600000\": 0.12232584, \"1471910400000\": 0.0968727, \"1467676800000\": 0.23253364, \"1469491200000\": 0.12632584, \"1470182400000\": 0.0101031, \"1467936000000\": 0.24953364}}'"
      }
     ],
     "trading_days": ""
    },
    {
     "cell_type": "markdown",
     "id": "DE9F4818C5214F638F9048BA407CBF78",
     "metadata": {},
     "source": [
      "## 2 \u4f7f\u7528\u4f18\u77ff\u4e13\u4e1a\u7248\u7684\u7ec4\u5408\u5206\u6790\u5de5\u5177\u8fdb\u884c\u7b56\u7565\u5206\u6790\n",
      "---\n",
      "### 2.1 gen_drawdown_table\n",
      "\u8be5\u51fd\u6570\u5bf9\u7b56\u7565\u7684\u56de\u64a4\u671f\u8fdb\u884c\u4e86\u5f52\u7eb3"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "id": "7D4FB208CCF64C819D1AD745E6C5E849",
     "input": [
      "returns = perf['returns']\n",
      "returns.index = pd.to_datetime(returns.index)\n",
      "gen_drawdown_table(returns)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>net drawdown in %</th>\n",
        "      <th>peak date</th>\n",
        "      <th>valley date</th>\n",
        "      <th>recovery date</th>\n",
        "      <th>duration</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>31.3717</td>\n",
        "      <td>2016-07-13</td>\n",
        "      <td>2016-07-29</td>\n",
        "      <td>NaT</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>17.8365</td>\n",
        "      <td>2016-06-13</td>\n",
        "      <td>2016-06-24</td>\n",
        "      <td>2016-07-04</td>\n",
        "      <td>16</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>3.25517</td>\n",
        "      <td>2016-07-04</td>\n",
        "      <td>2016-07-06</td>\n",
        "      <td>2016-07-11</td>\n",
        "      <td>6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>0</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>0</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>0</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>0</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>0</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>0</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>0</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>2016-06-01</td>\n",
        "      <td>1</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "  net drawdown in %  peak date valley date recovery date duration\n",
        "0           31.3717 2016-07-13  2016-07-29           NaT      NaN\n",
        "1           17.8365 2016-06-13  2016-06-24    2016-07-04       16\n",
        "2           3.25517 2016-07-04  2016-07-06    2016-07-11        6\n",
        "3                 0 2016-06-01  2016-06-01    2016-06-01        1\n",
        "4                 0 2016-06-01  2016-06-01    2016-06-01        1\n",
        "5                 0 2016-06-01  2016-06-01    2016-06-01        1\n",
        "6                 0 2016-06-01  2016-06-01    2016-06-01        1\n",
        "7                 0 2016-06-01  2016-06-01    2016-06-01        1\n",
        "8                 0 2016-06-01  2016-06-01    2016-06-01        1\n",
        "9                 0 2016-06-01  2016-06-01    2016-06-01        1"
       ]
      }
     ]
    },
    {
     "cell_type": "markdown",
     "id": "1F463FFFD0CA4F51B2422CDCAD45BE77",
     "metadata": {},
     "source": [
      "\u4e0a\u8868\u7ed9\u51fa\u4e86\u4e0d\u540c\u7684\u56de\u64a4\u671f\uff0c\u4f8b\u5982\u4ece2016\u5e747\u67084\u53f7\u52302016\u5e747\u67086\u53f7\uff0c\u7b56\u7565\u53d1\u751f\u4e86\u56de\u64a4\uff0c2016\u5e747\u67086\u65e5\u4e4b\u540e\u7b56\u7565\u91cd\u65b0\u76c8\u5229\uff0c\u76f4\u52302016\u5e747\u670811\u53f7\u7ec4\u5408\u7d2f\u8ba1\u6536\u76ca\u7387\u6062\u590d\u81f3\u56de\u64a4\u524d\u7684\u6c34\u5e73\u3002"
     ]
    },
    {
     "cell_type": "markdown",
     "id": "7CF63A0FFD384E7C8DEE80CD4E8309BD",
     "metadata": {},
     "source": [
      "### 2.2 plot_drawdown_periods\n",
      "\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8c03\u7528plot_drawdown_periods\u51fd\u6570\u66f4\u52a0\u76f4\u89c2\u7684\u5bf9\u4e0a\u8868\u8fdb\u884c\u5c55\u793a\u3002"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "id": "379F98CD1D05466F84F3390A9C470C8F",
     "input": [
      "fig = plt.figure(figsize=(8, 4))\n",
      "ax = fig.add_subplot(111)\n",
      "ax = plot_drawdown_periods(returns, top=1, ax=ax)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "data": {
        "image/png": 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lyqd56aVV6HQ6QkPDWLny/2zyPQohhOhaZPUzK8lqPc3J/WhO7kdzcj+ak/vRnNyP5mT1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\nBUD37t3Jzc3lvffe45133uHbb78lICAAnU6HpaWlMkyeXq9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        "text/plain": "<matplotlib.figure.Figure at 0x8fb7a50>"
       },
       "metadata": {},
       "output_type": "display_data",
       "png": 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lyqd56aVV6HQ6QkPDWLny/2zyPQohhOhaZPUzK8lqPc3J/WhO7kdzcj+ak/vRnNyP5mT1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\n",
       "source": "display",
       "text": [
        "<matplotlib.figure.Figure at 0x8fb7a50>"
       ]
      }
     ]
    },
    {
     "cell_type": "markdown",
     "id": "282505FF6A3748F9962662CCD311DD4E",
     "metadata": {},
     "source": [
      "\u53c2\u6570returns\u4e3a\u7d2f\u8ba1\u6536\u76ca\u7387\u5e8f\u5217\uff0ctop\u6765\u6307\u5b9a\u9700\u8981\u7ed8\u5236\u591a\u5c11\u4e2a\u56de\u64a4\u671f\uff08\u4ece\u5927\u5230\u5c0f\u6392\u5217\uff09"
     ]
    },
    {
     "cell_type": "markdown",
     "id": "46B4835DA51C42E9A5A3809EECD76C1E",
     "metadata": {},
     "source": [
      "### 2.3 plot_drawdown_underwater\n",
      "\u8be5\u51fd\u6570\u7ed8\u5236\u4e86\u5f53\u524d\u65f6\u95f4\u8282\u70b9\u4e0b\u7684\u7b56\u7565\u7684\u56de\u64a4\u3002"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "id": "A9037169C9954F188CFCD06DF562D99C",
     "input": [
      "ax = plot_drawdown_underwater(perf['returns'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "data": {
        "image/png": 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Anj17mDZtGpMnTyYQCHD55Zfz1FNPoZTCtv0CJ7FYDMuy2L59OzfccAOmKUO0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\n4QshhBBe4P8BFw/lmRhM5mAAAAAASUVORK5CYII=\n",
        "text/plain": "<matplotlib.figure.Figure at 0x8fb7710>"
       },
       "metadata": {},
       "output_type": "display_data",
       "png": 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Anj17mDZtGpMnTyYQCHD55Zfz1FNPoZTCtv0CJ7FYDMuy2L59OzfccAOmKUO0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\n4QshhBBe4P8BFw/lmRhM5mAAAAAASUVORK5CYII=\n",
       "source": "display",
       "text": [
        "<matplotlib.figure.Figure at 0x8fb7710>"
       ]
      }
     ]
    },
    {
     "cell_type": "markdown",
     "id": "CDEC5D6AC51C4733865E909C335F1895",
     "metadata": {},
     "source": [
      "### 2.4 plot_monthly_returns_heatmap\n",
      "\u8be5\u51fd\u6570\u7ed8\u5236\u4e86\u7b56\u7565\u6bcf\u4e2a\u6708\u7684\u6536\u76ca\u3002\u76f8\u5bf9\u800c\u8a00\uff0c\u5bf9\u4e00\u4e9b\u6708\u5ea6\u8c03\u4ed3\u7684\u80a1\u7968\u7b56\u7565\uff0c\u4f7f\u7528\u8be5\u56fe\u8fdb\u884c\u5206\u6790\u66f4\u52a0\u6709\u7528\u3002"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "id": "1BC9A5E4C981457C8DBEB72C75F728EF",
     "input": [
      "ax = plot_monthly_returns_heatmap(returns)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "data": {
        "image/png": 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+nAzFdXr1UmWtX6mqw8f9e9HlUuWBw3Tsmf+R51y2/4ZDoQ6eOKr2sx7TmfPZat+kpSZ2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\nUkwMoDCcYQPXsfD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        "text/plain": "<matplotlib.figure.Figure at 0x8739a90>"
       },
       "metadata": {},
       "output_type": "display_data",
       "png": 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wcI0cOVIPPfSQz3qrVq20dOlSSRfeg16zZo3i4+OLPF5ISIhOnTp1VWYFcHkE\nG7gOXXwG3atXL0VGRvpsf/jhhyVJCQkJuv/++5WYmKjWrVtfsu+vv+7du7deeukln5vOAJQNfr0m\nAAAGcIYNAIABBBsAAAMINgAABhBsAAAMINgAABhAsAEAMIBgAwBgAMEGAMCA/wcxi2UWcjqI+wAA\nAABJRU5ErkJggg==\n",
       "source": "display",
       "text": [
        "<matplotlib.figure.Figure at 0x8739a90>"
       ]
      }
     ]
    },
    {
     "cell_type": "markdown",
     "id": "1A9D1648B942474F83393928E594760D",
     "metadata": {},
     "source": [
      "### 2.5 plot_monthly_returns_dist\n",
      "\u7ed8\u5236\u6708\u5ea6\u6536\u76ca\u7684\u5206\u5e03\u56fe"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "id": "F78982F1AABB4C0C82F6B2AFD14BFB9C",
     "input": [
      "ax = plot_monthly_returns_dist(returns)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "data": {
        "image/png": 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        "text/plain": "<matplotlib.figure.Figure at 0x8764410>"
       },
       "metadata": {},
       "output_type": "display_data",
       "png": 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2lSR16NBBWVlZHg8MAKoTmt/Y4R8A1zgt+qWlpWrTpo3DOqvV6rGAAACAZzgt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\n6AMAYBIUfQAATIKiDwCASVD0AQAwif8HM2QleuAMCkAAAAAASUVORK5CYII=\n",
       "source": "display",
       "text": [
        "<matplotlib.figure.Figure at 0x8764410>"
       ]
      }
     ]
    }
   ],
   "metadata": {}
  }
 ]
}